Applications in Parallel MATLAB

The parallel MATLAB implementations used for this project are MatlabMPI and pMATLAB, both developed by Dr. Jeremy Kepner at MIT-LL. MatlabMPI is based on the message passing interface standard, in which processes coordinate their work and communicate by passing messages among themselves. The pMATLAB library supports parallel array programming in MATLAB. The user program defines arrays that are distributed among the available processes. Although communication between processes is actually done through message passing, the details are hidden from the user. The objective of this PET project was to develop parallel MATLAB code for selected algorithms that are of interest to the Department of Defense (DoD) signal/image processing (SIP) community and to run the code on the HPCMP systems. The algorithms selected for parallel MATLAB implementation were a support vector machine (SVM) classifier, metropolis-Hastings Markov chain Monte Carlo (MCMC) simulation, and content-based image compression (CBIC)